The next wave of AI isn't just about single-function tools. It's about agents that act like team members, executing complex, multi-step tasks like competitor research, ad creation, and performance analysis based on a single prompt.

Companies struggle with AI not because of the models, but because their data is siloed. Adopting an 'integration-first' mindset is crucial for creating the unified data foundation AI requires.

AI's most significant impact is not just campaign optimization but its ability to break down data silos. By combining loyalty, e-commerce, and in-store interaction data, retailers can create a holistic customer view, enabling truly adaptive and intelligent marketing across all channels.

AI models for campaign creation are only as good as the data they ingest. Inaccurate or siloed data on accounts, contacts, and ad performance prevents AI from developing optimal strategies, rendering the technology ineffective for scalable, high-quality output.

Marketing leaders pressured to adopt AI are discovering the primary obstacle isn't the technology, but their own internal data infrastructure. Siloed, inconsistently structured data across teams prevents them from effectively leveraging AI for consumer insights and business growth.

The current landscape of third-party AI marketing tools is immature compared to sales or support. Most solutions focus narrowly on content generation and lack the sophisticated data analysis and campaign orchestration capabilities needed for a true go-to-market engine.

View AI less as a tool for discrete tasks and more as the foundation for a central marketing hub. This system uses AI to create and maintain branded playbooks for all marketing activities, ensuring consistency and quality regardless of who is executing the work.

Companies struggle to get value from AI because their data is fragmented across different systems (ERP, CRM, finance) with poor integrity. The primary challenge isn't the AI models themselves, but integrating these disparate data sets into a unified platform that agents can act upon.

According to Salesforce's AI chief, the primary challenge for large companies deploying AI is harmonizing data across siloed departments, like sales and marketing. AI cannot operate effectively without connected, unified data, making data integration the crucial first step before any advanced AI implementation.